Target layer state estimation in multilayer complex dynamical networks using functional observability |
| |
| Institution: | 1. College of Automation and College of Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing 210023, PR China;2. Jiangsu Engineering Lab for IOT Intelligent Robots (IOTRobot), Nanjing 210023, PR China;1. Department of Automation, Xiamen University, Xiamen, Fujian 361005, China;2. School of Systems Design and Intelligent Manufacturing, South University of Science and Technology, Shenzhen Guangdong 518000, China |
| |
| Abstract: | In large-scale complex dynamical networks, it is significant to estimate the states of target nodes with only a part of measured nodes. Meanwhile, multilayer complex dynamical networks exist widely in society and engineering. Therefore, it has important theoretic meaning and practical value to study the state estimation of target nodes in multilayer complex dynamical networks with limited node measurements. In this paper, with the measurable state information of a portion of nodes in one layer in the multilayer complex dynamical network, the state estimation of target nodes in other layers is studied. First, we build the model of the multilayer complex dynamical network which includes some target nodes and sensor nodes. Second, auxiliary nodes are selected by using the maximum matching principle in graph theory to construct the augmented node set. Third, we discuss the relationship between the minimum number of auxiliary nodes and interlayer connection probability in the multilayer complex dynamical network. Forth, an appropriate functional state observer is designed with limited number of measured nodes according to a typical model-based algorithm. Finally, numerical simulations are given to demonstrate the accuracy of the proposed method. The proposed method can achieve the accurate estimation with less placement of observers and fewer computational costs in the multilayer complex dynamical network. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
